From cd3a2f3e745ba9d984e2f48b8350c806ddf60069 Mon Sep 17 00:00:00 2001
From: markus holzer <markus.holzer@fau.de>
Date: Mon, 10 Aug 2020 07:49:29 +0200
Subject: [PATCH] Added test cases to vectorisation
---
pystencils_tests/test_vectorization.py | 85 ++++++++++++++++++++++++--
1 file changed, 81 insertions(+), 4 deletions(-)
diff --git a/pystencils_tests/test_vectorization.py b/pystencils_tests/test_vectorization.py
index 1fa1812eb..3cc1be4f3 100644
--- a/pystencils_tests/test_vectorization.py
+++ b/pystencils_tests/test_vectorization.py
@@ -4,6 +4,7 @@ import sympy as sp
import pystencils as ps
from pystencils.backends.simd_instruction_sets import get_supported_instruction_sets
from pystencils.cpu.vectorization import vectorize
+from pystencils.fast_approximation import insert_fast_sqrts, insert_fast_divisions
from pystencils.transformations import replace_inner_stride_with_one
@@ -109,7 +110,6 @@ def test_piecewise1():
def test_piecewise2():
-
arr = np.zeros((20, 20))
@ps.kernel
@@ -128,7 +128,6 @@ def test_piecewise2():
def test_piecewise3():
-
arr = np.zeros((22, 22))
@ps.kernel
@@ -146,12 +145,32 @@ def test_logical_operators():
arr = np.zeros((22, 22))
@ps.kernel
- def test_kernel(s):
+ def kernel_and(s):
f, g = ps.fields(f=arr, g=arr)
s.c @= sp.And(f[0, 1] < 0.0, f[1, 0] < 0.0)
g[0, 0] @= sp.Piecewise([1.0 / f[1, 0], s.c], [1.0, True])
- ast = ps.create_kernel(test_kernel)
+ ast = ps.create_kernel(kernel_and)
+ vectorize(ast)
+ ast.compile()
+
+ @ps.kernel
+ def kernel_or(s):
+ f, g = ps.fields(f=arr, g=arr)
+ s.c @= sp.Or(f[0, 1] < 0.0, f[1, 0] < 0.0)
+ g[0, 0] @= sp.Piecewise([1.0 / f[1, 0], s.c], [1.0, True])
+
+ ast = ps.create_kernel(kernel_or)
+ vectorize(ast)
+ ast.compile()
+
+ @ps.kernel
+ def kernel_equal(s):
+ f, g = ps.fields(f=arr, g=arr)
+ s.c @= sp.Eq(f[0, 1], 2.0)
+ g[0, 0] @= sp.Piecewise([1.0 / f[1, 0], s.c], [1.0, True])
+
+ ast = ps.create_kernel(kernel_equal)
vectorize(ast)
ast.compile()
@@ -159,3 +178,61 @@ def test_logical_operators():
def test_hardware_query():
instruction_sets = get_supported_instruction_sets()
assert 'sse' in instruction_sets
+
+
+def test_vectorised_pow():
+ arr = np.zeros((24, 24))
+ f, g = ps.fields(f=arr, g=arr)
+
+ as1 = ps.Assignment(g[0, 0], sp.Pow(f[0, 0], 2))
+ as2 = ps.Assignment(g[0, 0], sp.Pow(f[0, 0], 0.5))
+ as3 = ps.Assignment(g[0, 0], sp.Pow(f[0, 0], -0.5))
+ as4 = ps.Assignment(g[0, 0], sp.Pow(f[0, 0], 4))
+ as5 = ps.Assignment(g[0, 0], sp.Pow(f[0, 0], -4))
+ as6 = ps.Assignment(g[0, 0], sp.Pow(f[0, 0], -1))
+
+ ast = ps.create_kernel(as1)
+ vectorize(ast)
+ ast.compile()
+
+ ast = ps.create_kernel(as2)
+ vectorize(ast)
+ ast.compile()
+
+ ast = ps.create_kernel(as3)
+ vectorize(ast)
+ ast.compile()
+
+ ast = ps.create_kernel(as4)
+ vectorize(ast)
+ ast.compile()
+
+ ast = ps.create_kernel(as5)
+ vectorize(ast)
+ ast.compile()
+
+ ast = ps.create_kernel(as6)
+ vectorize(ast)
+ ast.compile()
+
+
+def test_vectorised_fast_approximations():
+ arr = np.zeros((24, 24))
+ f, g = ps.fields(f=arr, g=arr)
+
+ expr = sp.sqrt(f[0, 0] + f[1, 0])
+ assignment = ps.Assignment(g[0, 0], insert_fast_sqrts(expr))
+ ast = ps.create_kernel(assignment)
+ vectorize(ast)
+ ast.compile()
+
+ expr = f[0, 0] / f[1, 0]
+ assignment = ps.Assignment(g[0, 0], insert_fast_divisions(expr))
+ ast = ps.create_kernel(assignment)
+ vectorize(ast)
+ ast.compile()
+
+ assignment = ps.Assignment(sp.Symbol("tmp"), 3 / sp.sqrt(f[0, 0] + f[1, 0]))
+ ast = ps.create_kernel(insert_fast_sqrts(assignment))
+ vectorize(ast)
+ ast.compile()
--
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